This paper presents a brief survey of robotic caging and its applications. Caging is a kind of grasping methods, which can be accomplished geometrically by position-controlled robotic agents, and has advantages over conventional manipulation which requires to fulfill mechanical conditions. Due to the advantages, caging was extensively studied and applied in robotics. This paper reviews the robotic literature related to caging ranging from its historical background, state-of-the-art developments, to practical applications. It provides our insights on some open problems and promising research and application directions. We hope the paper could help researchers quickly catch the strength and limitations of caging, and make impacting contributions to the research community.

A survey of robotic caging and its applications

In this paper, the problem of object caging and transporting is considered for multiple mobile robots. With the consideration of minimizing the number of robots and decreasing the rotation of the object, the proper points are calculated and assigned to the multiple mobile robots to allow them to form a symmetric caging formation. The caging formation guarantees that all of the Euclidean distances between any two adjacent robots are smaller than the minimal width of the polygonal object so that the object cannot escape. In order to avoid collision among robots, the parameter of the robots radius is utilized to design the caging formation, and the A⁎ algorithm is used so that mobile robots can move to the proper points. In order to avoid obstacles, the robots and the object are regarded as a rigid body to apply artificial potential field method. The fuzzy sliding mode control method is applied for tracking control of the nonholonomic mobile robots. Finally, the simulation and experimental results show that multiple mobile robots are able to cage and transport the polygonal object to the goal position, avoiding obstacles.

Symmetric caging formation for convex polygonal object transportation by multiple mobile robots based on fuzzy sliding mode control

In this paper, the problem of object caging and transporting is considered by multiple mobile robots using object closure technology. With the consideration of minimizing the number of the robots and decreasing the rotation of the object, the proper points are calculated and assigned to the multiple mobile robots to form the symmetric caging formation. The caging formation guarantees that all of the Euclidean distances between two adjacent robots are smaller than the minimal width of the polygon object and the object cannot escape. Finally, the simulation results represent multiple mobile robots which cage and transport the polygon object to the goal position.

Symmetric caging formation for convex polygon object transportation by multiple mobile robots

This paper presents transporting algorithm for multiple robots to transport a concave or convex object. The object transporting includes three processes: calculating proper points process; approaching proper points process; and transporting an object process. Using fuzzy sliding mode control algorithm, we design a kinematic velocity controller. We also propose a dynamic torque controller by adaptive sliding mode control algorithm. Finally, simulations and experiment show good performance of proposed methods.

/pdf/multiple-robots-motion-control-to-transport-an-object-8vtk6lzhdt.pdf

Multiple robots motion control to transport an object

A conventional way to find a proper grasp to grab and hold any object is to measure its stability which usually is based on physical constraint called force-closure. This execution works well from the theoretical point of view but often fails on an actual robot due to many reasons such as intrinsic errors in robot?s system and a disparity between real and simulated physics. Several research works introduced methods to alleviate those issues and increase the success rate of grasping for a real robot. Caging and Independent Contact Region are ones of them. In this work, we investigate a method to find a grasp that is more stable and robust by combining those two techniques which result in a learning-based approach that utilizes an artificial neural network to find a proper grasp based on those techniques and some heuristic methods.

Efficient and robust grasp planning based on independent contact region and caging

An object is said to be caged when it is bounded within some confined workspace, in which it may move but cannot escape from. An object in a cage formed by multiple robots can be transported as the robot caging formation moves. Unlike traditional contact based approach, this non-prehensile transportation strategy puts much less stringent requirement on robot synchronization and object dynamics prediction. This paper proposes a heuristic method for computing a caging formation of a given polygonal object. Existing caging computation is either for a fixed number of robots or assuming unlimited number of robots. Our goal is different. The user is allowed to choose how loosely the object may move in its cage. With the given level of looseness, the proposed method computes where the robots should be placed. We also present simulation results confirming the validity of the approach.

A heuristic method for computing caging formation of polygonal object

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A heuristic method for computing caging formation of polygonal object